{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring"}],"enrichment":{"capability":"Adds distributed tracing to MCP (Model Context Protocol) agentic workflows by instrumenting the MCP Python SDK to emit OpenTelemetry spans tracking tool calls, prompts, and completions.","skillfed_tags":["observability","mcp-instrumentation","agentic-ai"],"use_cases":["Debug agentic workflows by viewing the full trace of tool calls, prompts, and LLM responses in your observability backend.","Monitor production MCP applications to detect tool call failures, latency spikes, or unexpected LLM behavior.","Evaluate agent performance by analyzing spans to understand which tools are called most frequently and how long each step takes.","Reduce trace volume in privacy-sensitive environments by disabling content logging while keeping structural tracing intact."],"what_it_does":"This package integrates the MCP Python SDK with OpenTelemetry to emit distributed traces from agentic workflows. When you call `McpInstrumentor().instrument()`, it hooks into MCP framework calls to generate spans that track tool invocations, prompts sent to LLMs, and completions received\u2014giving you visibility into how your agent is using tools and interacting with language models.\n\nBy default, the instrumentation logs the actual content of prompts, completions, and embeddings to span attributes, which helps with debugging and evaluation but may expose sensitive user data. You can disable this by setting `TRACELOOP_TRACE_CONTENT=false` to reduce trace size and protect privacy. The package depends on the OpenTelemetry API and instrumentation base libraries, plus semantic convention definitions for AI workloads.","worth_installing":"Yes, if you are building or running MCP-based agentic workflows and need observability. The package is actively maintained, has no known vulnerabilities, and integrates cleanly into the OpenTelemetry ecosystem. Install it when you want to trace tool calls and LLM interactions; skip it if you have no observability infrastructure or are not using the MCP framework."},"id":"opentelemetry-instrumentation-mcp","links":{"html":"https://skillfed.io/packages/opentelemetry-instrumentation-mcp","md":"https://skillfed.io/packages/opentelemetry-instrumentation-mcp.md","pypi":"https://pypi.org/project/opentelemetry-instrumentation-mcp/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"opentelemetry-instrumentation-mcp","python_support":"supports_current","summary":"OpenTelemetry mcp instrumentation"},"popularity":{"monthly_downloads":6716888,"position":1865,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.62.3"}